AI Coding

A great example from the article on the benefits of "getting freaky" and experimenting with different architectural ideas:

To see why this matters, let’s look at a miniature example: building a collaborative document editor.

Team Standard uses the default AI stack. They prompt Cursor to build a React frontend with a Node.js backend and PostgreSQL. The AI generates it perfectly. But as users start collaborating, they hit race conditions. Team Standard responds by throwing money at the problem— adding Redis pub/sub, writing complex conflict resolution logic in JavaScript, and spending weeks debugging edge cases where a user’s cursor inexplicably deletes an entire paragraph. Their feedback latency is massive because the architecture fights the inherent reality of distributed users.

Team Weird decides to use a Local-First architecture with CRDTs. The learning curve is brutal. They have to deeply understand distributed state. But once they cross that threshold, they use AI to generate the boilerplate for their CRDT data structures. The result? Every user edits locally with zero latency. Syncing happens silently in the background. If the server goes down, nobody notices.

Team Standard shipped faster. Team Weird shipped a fundamentally superior product that Team Standard cannot easily copy without rewriting their entire architecture from scratch.